Welcome to Adwait's Homepage

Adwait Jog, Ph.D. (Penn State)    Assistant Professor    Department of Computer Science    William & Mary    McGlothlin-Street Hall 111    Williamsburg, VA 23187     ajog@wm.edu, Google Scholar Profile

About

I am an assistant professor in the Department of Computer Science at William & Mary in Virginia, USA. At William & Mary, I am leading the Insight Computer Architecture Lab. Our goal is to generate insights necessary in order to architect future computers that are more energy-efficient, capable, reliable, and secure.

I am always looking for self-motivated students to join my lab. Interested students can email me with questions. If you are not at William & Mary, please formally apply to the Ph.D. program at CS department.

A high-level summary of my group's research can be found here and here.

Recent and Selected Publications (complete list)

• (DSN 2021) Data-centric Reliability Management in GPUs

• (SIGMETRICS 2021) SUGAR: Speeding Up GPGPU Application Resilience Estimation with Input Sizing

• (HPCA 2021) Analyzing and Leveraging Decoupled L1 Caches in GPUs

• (PACT 2020) Analyzing and Leveraging Shared L1 Caches in GPUs

• (ASPLOS 2020) Why GPUs are Slow at Executing NFAs and How to Make them Faster

• (HPCA 2020) BCoal: Bucketing-based Memory Coalescing for Efficient and Secure GPUs

• (PACT 2019) Analyzing and Leveraging Remote-core Bandwidth for Enhanced Performance in GPUs

• (DSN 2019) Exploiting Latency and Error Tolerance of GPGPU Applications for an Energy-efficient DRAM

• (ICS 2019) Address-Stride Assisted Approximate Value Prediction in GPUs

• (ISCA 2019) Opportunistic Computing in GPU Architectures

• (SIGMETRICS 2019) Quantifying Data Locality in Dynamic Parallelism in GPUs

• (MICRO 2018) Architectural Support for Efficient Large-Scale Automata Processing

• (MICRO 2018) Fault Site Pruning for Practical Reliability Analysis of GPGPU Applications

• (HPCA 2018) Efficient and Fair Multi-programming in GPUs via Effective Bandwidth Management

• (HPCA 2018) RCoal: Mitigating GPU Timing Attack via Subwarp-based Randomized Coalescing Techniques

• (ASPLOS 2018) MASK: Redesigning the GPU Memory Hierarchy to Support Multi-Application Concurrency

Current Research Funding

My research group is currently supported by the following research grants:

• Google Research Scholar Award. Thanks Google!

• DOE/ANL Funding. Thanks ANL!

• NSF CAREER Award 2018. News in the Media. Thanks NSF!

• NSF SHF Award 2017. Thanks NSF!

• NVIDIA Equipment Donation. Thanks NVIDIA!

Currently Teaching (complete list)

• Spring 2021: CSCI 424/524, Computer Architecture (undergraduate course)

Recent Committees (complete list)

• Organization Committees: PACT 2020 (ACM SRC chair), GPGPU 2020 (Workshop co-chair), MICRO 2019 (Publicity co-chair), CGO 2019 (Publicity chair), GPGPU 2019 (Workshop co-chair)

• Program Committees: ASPLOS 2022, MICRO 2021, ISCA 2021, DSN 2021, HPCA 2021, HPCA 2020, MICRO 2020 (ERC), ISCA 2020 (ERC), ASPLOS 2020 (ERC), MICRO 2019, SIGMETRICS 2019, ICCD 2019, HPDC 2019, HPCA 2019 (ERC), NAS 2019.

• W&M Committees (2020-21): Graduate Admissions, Graduate Curriculum, CS Colloquiums, Pre-major advising